Extraprostatic Seed Placement and Its Effect on Seed Loss
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to examine the relationship between extraprostatic seed placement and seed loss in a cohort of patients who had underwent both computed tomographic (CT) and magnetic resonance (MR) scans at day 0 and day 30 following brachytherapy. MATERIALS AND METHODS: Twenty-two patients with 1997 AJC clinical stage T1-T2 prostatic carcinoma were implanted with nonstranded I 125. Patients were selected solely by having a prostate volume between 15 and 60 cc and a willingness to return for 30-day follow-up CT and MR scans. The total number of I-125 sources implanted on day 0 ranged from 50 to 104 (median: 70). Preplan treatment planning methods have been previously described in detail: a modified peripheral loading pattern and treatment margins of 5-10 mm were used. Noncontrast postimplantation CT and MR scans were obtained 1-4 hours after implantation on day 0. The total seed count on days 0 and 30 was verified by plain radiograph. Pelvic MR (T1) images were registered with the CT images in the Varian planning system, using bony landmarks. The number of extracapsular seeds in each quadrant of the circumference was then totaled for each patient. A second set of plain radiographs (for seed counting), as well as CT and MR scans, were obtained 30 days after implantation (day 30) and were similarly analyzed. RESULTS: The number of extraprostatic seeds at day 0 ranged from 13 to 35, making up 17%-48% (median: 34%) of the total number implanted. Of the 22 patients, 10 lost one or more seeds between the implantation day and the 1-month follow-up. The mean number of seeds lost was 1.1 (+/- 1.7). There was no apparent relationship between the percent of extraprostatic seeds and the number of seeds lost. There was no apparent relationship between seed loss and number of seeds less than 3 mm or greater than 3 mm from the prostatic capsule. CONCLUSIONS: We have shown here that with CT and MR seed localization, extraprostatic seed placement does not appear to substantially increase the likelihood of seed loss after the procedure.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".